Nonostante una lunga tradizione di studi, le emozioni costituiscono ancora oggi un oggetto per molti aspetti poco definito. In particolare, pochi risultati confermati sono disponibili per l'espressione vocale delle emozioni e per i suoi aspetti fisiologici. Questa assenza di risultati può essere spiegata attraverso l'adozione della teoria processuale componenziale di Scherer. Secondo questo modello l'emozione sarebbe un processo che si sviluppa in e attraverso alcune componenti, tra cui quella espressiva e quella fisiologica. Pertanto una comprensione delle emozioni è possibile solo attraverso un approccio che sia multi-componenziale. Tre studi sono stati condotti. Il primo ha indagato l'espressione delle emozioni, identificando alcune delle previsioni del modello componenziale per la produzione vocale. Il secondo ha analizzato in termini di sistema nervoso autonomo gli aspetti fisiologici dell'esperienza emotiva, sostenendo la funzione di mobilitazione delle risorse della componente. Il terzo studio ha posto in relazione queste due componenti cercando di identificare alcuni aspetti del loro funzionamento integrato e interdipendente. Infine, è suggerita l'adozione di un modello processuale componenziale alla tematica del riconoscimento emotivo automatico, inerente al tema dell'affective computing. / Even if emotion has been studied for many years, it still remains quite unknown in some aspects. Among others, vocal expression and physiology of emotions produced very few widely accepted results. Such an outcome can be explained through the adoption of the component process model of emotion by Scherer. In his theory emotions are processes in which a number of different components are involved, among others expressive and physiological ones. As a consequence emotions can be explained only through a multi-component approach. Three studies are performed. The first investigated emotional expression, finding some correspondences with component predictive model for vocal expression. The second analyzed autonomic activity of emotions, sustaining its function of resources mobilization. The third combined the two components, finding some aspects of their integration and inter-dependency. Finally, concerning affective computing paradigm, a componential approach to emotion automatic recognition is suggested.

While several approaches exist for modeling goals and business processes in organizations, the relationships between these two views are often not well defined. This inhibits the effective reuse of available knowledge in models. This thesis aims to address this issue through the introduction of a Goal-oriented Pattern Family (GoPF) framework that helps constructing business process models from organization goals while expanding these goals, establishing traceability relationships between the goal and process views, and improving reusability. Methods for extracting domain knowledge as patterns, which are composed of goal model building blocks, process model building blocks, and their relationships, and for maintaining the patterns over time are also presented. The GoPF framework provides the infrastructure for defining pattern families, i.e., collections of related patterns for particular domains. The foundation of GoPF is formalized as a profile of the User Requirements Notation, a standard modeling language that supports goals, scenarios, and links between them. A method for the use of GoPF is defined and then illustrated through a case study that targets the improvement of patient safety in healthcare organizations. The framework and the extraction/maintenance methods are also validated against another case study involving aviation security in a regulatory environment. The GoPF framework is expected to have a positive impact on the scientific community through the formalization, evolution, and reuse of patterns in domain-specific business domains. From an industrial viewpoint, this framework will also help intermediary organizations (such as consulting firms) who are required to repeatedly create and document goal and process models for other organizations in their business domain.

Business process modeling is utilized by organizations for defining and reengineering their business processes. On the other hand, software requirements analysis activities are performed for determining the system boundaries, specifying software requirements using system requirements and resolving conflicts between requirements. From this point of view, these two activities are considered in different disciplines. An organization requiring its business processes to be defined and supported with information systems would benefit from performing business process modeling and requirements analysis concurrently. In this study, an approach enabling concurrent execution of business process modeling and requirements analysis is developed. The approach includes two business process modeling notations adapted to the research needs, a process defining the steps for implementing the approach and the requirements generation tool that generates natural language specification documents by using business process models. Within this study, two case studies are introduced / one describing the development of the approach and the other exploring if the total efficiency of performing business process modeling and requirements analysis activites would be increased by using the approach.

Der steigende Effizienzdruck in der Automobilindustrie führt zu der Notwendigkeit bereits in der frühen Planungsphase umfassende Aussagen in Bezug auf die Leistungsfähigkeit des entworfenen Systems zu machen. In der vorliegenden Arbeit wird für den Fertigungsbereich Karosseriebau ein Kennzahlensystem entwickelt, das eine fundierte Entscheidungsbasis für das Management bietet und den Fertigungsplaner mit detaillierten Informationen zur Erkennung von Schwachstellen versorgt. Zur Beherrschung des komplexen Gesamtsystems wird zunächst ein hierarchisches Prozessmodell erarbeitet, anhand dessen die wesentlichen Erfolgsfaktoren des Karosseriebaus identifiziert und parametriert werden. Die Kennzahlen werden definiert und entsprechend ihrer Ursache-Wirkungs-Beziehungen in einem durchgängigen, modularen Kennzahlensystem angeordnet. Zur Sicherung der Praxistauglichkeit werden bei der Entwicklung des Kennzahlensystems der Kennzahlenbedarf und die Kennzahlenverfügbarkeit über den Projektverlauf berücksichtigt. Die Berechnung und Komprimierung der Kennzahlen sowie die Visualisierung der Leistungsentwicklung werden in die Digitale Fabrik integriert und so der manuelle Pflegeaufwand reduziert. Der Nutzen des Kennzahlensystems in der Unternehmerischen Praxis wird anhand von Beispielen verdeutlicht und nachgewiesen.

End of life (EOL) caregiving can be a daunting and challenging endeavor as caregivers adjust to the ever-changing care demands associated with dying. Increased personal care, assisting with symptom and medication management, and attending to the emotional and spiritual needs of the dying person require caregivers to learn new tasks and to assume new roles such as social worker, nurse, and chaplain. As families continue to play an essential role in meeting the health care needs of their dying loved ones, it is imperative for social workers to understand the complexities of the end of life caregiving experience in order to better serve this population. One way to better understand this experience is by examining it within the context of the stress process model of caregiving. This model provides a comprehensive way to examine the relationship among multiple risk and protective factors within the "caregiver-in-environment" context. Using a secondary dataset, the best fit predictive model of caregiver depression included a mix of sociodemographic characteristics, primary objective and subjective stressors, and mediating variables. Two protective factors, social support and the fulfillment of spiritual needs lessened the effects of caregiver depression among the most vulnerable caregivers. Findings from this study help to bridge the gap between theory and social work practice. The stress process model of caregiving is a well-tested theoretical model, which can be utilized to guide social workers in developing comprehensive assessment measures and interventions that target specific aspects and sources of stress within the EOL caregiving experience.

This study explored the effect of public relations message strategies on beliefs, attitudes, and behavioral intentions of individuals regarding boater safety. An experiment was conducted using seven safety messages. Specifically, Fishbein and Ajzen’s (1975) theory of reasoned action and J.E. Grunig’s (1997) situational theory of publics were used to examine the communication effects of message strategies proposed by Hazleton and Long’s (1988) public relations process model. The findings of this study support the predictions of the theory of reasoned action—that salient beliefs predict attitude toward behavior and attitude toward behavior and subjective norm predict behavioral intent. Of the three attitude items measured— attitude toward message, attitude toward issue, and attitude toward organization—salient beliefs had the greatest effect on the attitude toward issue measure. Subjective norm was shown to be the stronger predictor of the three attitude items. In addition, support was found for the predictions of the situational theory of publics. The independent variables—problem recognition, constraint recognition, and level of involvement—were found to predict information seeking behaviors. However, the use of public relations message strategies in boater safety communication produced minimal effects on the same variables. It was determined that the power strategies, threat and punishment and promise and reward, would be most effective when communicating to a passive public such as the sample tested in this study. This study is significant to public relations literature because it examined how active boaters and non-boaters perceive safety messages. There appeared to be no research on the use of safe boating messages. Thus, there was no research on how public relations messages about boater safety affect boaters’ attitudes, awareness, and behavioral intentions prior to the implementation of this study. Determining effective boater safety messages will help to reduce boater accidents, injuries, and fatalities in years to come (U.S. Coast Guard, 2009), making this study both necessary and original.

Utilizing communication and activist organization perspectives, this empirical study examined activist message strategies and how they influence variables related to the receiver of activist communication. Specifically, J.E. Grunig's (1997) situational theory of publics and Fishbein and Ajzen's (1975) theory of reasoned action were used to explain the communication effects of the seven activist message strategies developed from Hazleton and Long's (1988) public relations process model. The findings of this study support the premise of situational theory of publics and contribute to the extension of the theory through the inclusion of goal compatibility as a predictor of information seeking behavior and the use of alternative items to operationalize information seeking behavior, such as visiting a Web site. Only partial support was found for the predictions of the theory of reasoned action. Attitude toward behavior was not found to have a significant influence on behavioral intent. However, the importance of subjective norm to the prediction of behavioral intent was reiterated. Also, the proposition that message strategies influence behavioral intent via their influence on attitude toward strategy was supported. Finally, results of this study partially supported the hypothesis that receiver variables are influenced by activist message strategies. Problem recognition, goal compatibility, attitude toward strategy, and attitude toward behavior were found to be affected by activist message strategies. Problem recognition was influenced most by the persuasive strategy, goal compatibility was most influenced by the threat and punishment strategy, and attitude toward strategy and attitude toward behavior were both influenced most by the cooperative problem-solving strategy. Overall, the results of this research suggest that, of the seven activist message strategies, activist organizations will be most successful using persuasive and coercive strategies. This important finding offers a recommendation to activist organizations regarding the most effective strategy to use in message development.

KM is the process of creating value from the intangible assets of an enterprise. It deals with how best to leverage knowledge internally in the enterprise (in its individual employees, and the knowledge that gets built into its structures and systems) and externally to the customers and stakeholders. As KM initiatives, projects and systems are just beginning to appear in organisations, there is little research and empirical field data to guide the successful development and implementation of such systems or to guide the expectations of the potential benefits of such systems. In addition, about 84 per cent of KM programmes failed or exerted no significant impact on the adopting organisations worldwide due to inability to consider many critical factors that contribute to the success of KM project implementation. Hence, this study is an exploratory investigation into the KM implementation based on an integrated approach. This includes: (1) a comprehensive review of the relevant literature; (2) a comprehensive analysis of secondary case studies of KM implementations in 90 organisations presented in the literature, in order to arrive at the most critical factors of KM implementation and their degree of criticality; (3) exploratory global survey of 92 organisations in 23 countries that have already implemented or are in the process of implementing KM; (4) in-depth case studies of four leading organisations to understand how KM implementation processes and the critical factors identified are being addressed. Based on the empirical findings of the study, 28 critical factors were identified that must be carefully considered in the KM implementation to achieve a successful project. Moreover, the study proposes an integrated model for effective KM implementation which contains essential elements that contribute to project success.

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The research objective of this thesis is to formulate and demonstrate a computational framework for modeling the design decisions of engineers. This framework is intended to be descriptive in nature as opposed to prescriptive or normative; the output of the model represents a plausible result of a designer's decision making process. The framework decomposes the decision into three elements: the problem statement, the designer's beliefs about the alternatives, and the designer's preferences. Multi-attribute utility theory is used to capture designer preferences for multiple objectives under uncertainty. Machine-learning techniques are used to store the designer's knowledge and to make Bayesian inferences regarding the attributes of alternatives. These models are integrated into the framework of a Markov decision process to simulate multiple sequential decisions. The overall framework enables the designer's decision problem to be transformed into an optimization problem statement; the simulated designer selects the alternative with the maximum expected utility. Although utility theory is typically viewed as a normative decision framework, the perspective in this research is that the approach can be used in a descriptive context for modeling rational and non-time critical decisions by engineering designers. This approach is intended to enable the formalisms of utility theory to be used to design human subjects experiments involving engineers in design organizations based on pairwise lotteries and other methods for preference elicitation. The results of these experiments would substantiate the selection of parameters in the model to enable it to be used to diagnose potential problems in engineering design projects. The purpose of the decision-making framework is to enable the development of a design process simulation of an organization involved in the development of a large-scale complex engineered system such as an aircraft or spacecraft. The decision model will allow researchers to determine the broader effects of individual engineering decisions on the aggregate dynamics of the design process and the resulting performance of the designed artifact itself. To illustrate the model's applicability in this context, the framework is demonstrated on three example problems: a one-dimensional decision problem, a multidimensional turbojet design problem, and a variable fidelity analysis problem. Individual utility functions are developed for designers in a requirements-driven design problem and then combined into a multi-attribute utility function. Gaussian process models are used to represent the designer's beliefs about the alternatives, and a custom covariance function is formulated to more accurately represent a designer's uncertainty in beliefs about the design attributes.